Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • News & Views
  • Published:

Mining the ultimate phenome repository

Nature Biotechnology volume 31, pages 1095–1097 (2013)Cite this article

Subjects

Combining genotyping and the data locked in medical records yields a large number of known genotype-phenotype associations.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Approaches for deriving associations between genetic variants and disease phenotypes.

References

  1. Denny, J.C. et al. Bioinformatics 26, 1205–1210 (2010).

    Article  CAS  Google Scholar 

  2. Denny, J.C. et al. Nat. Biotechnol. 31, 1102–1104 (2013).

    Article  CAS  Google Scholar 

  3. Denny, J.C. et al. Am. J. Hum. Genet. 89, 529–542 (2011).

    Article  CAS  Google Scholar 

  4. Hebbring, S.J. et al. Genes Immun. 14, 187–191 (2013).

    Article  CAS  Google Scholar 

  5. Liao, K.P. et al. Arthritis Rheum. 65, 571–581 (2013).

    Article  CAS  Google Scholar 

  6. Shameer, K. et al. Hum. Genet. doi:10.1007/s00439-013-1355-7 (2013).

  7. Blair, D.R. et al. Cell 155, 70–80 (2013).

    Article  CAS  Google Scholar 

  8. Leeper, N.J. et al. PLoS ONE 8, e63499 (2013).

    Article  CAS  Google Scholar 

  9. Frankovich, J., Longhurst, C.A. & Sutherland, S.M. N. Engl. J. Med. 365, 1758–1759 (2011).

    Article  CAS  Google Scholar 

  10. Newton, K.M. et al. J. Am. Med. Inform. Assoc. 20 e1, e147–e154 (2013).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Nigam H. Shah is at the Center for Biomedical Informatics Research, Stanford, California, USA.,

    Nigam H Shah

Authors
  1. Nigam H Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nigam H Shah.

Ethics declarations

Competing interests

The author declares no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shah, N. Mining the ultimate phenome repository. Nat Biotechnol 31, 1095–1097 (2013). https://doi.org/10.1038/nbt.2757

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.2757

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing